3 citations · 5 across the 10 of their papers we have counts for
11 papers
Online Inference in Distributional Temporal-Difference Learning
Yang Peng, Liangyu Zhang
We study online statistical inference for functionals of the return distribution under a fixed policy. The return distribution is estimated by nonparametric distributional temporal…
Variance-aware Reward Modeling with Anchor Guidance
Shuxing Fang, Ruijian Han, Liangyu Zhang +1
Standard Bradley--Terry (BT) reward models are limited when human preferences are pluralistic. Although soft preference labels preserve disagreement information, BT can only expres…
A Finite Sample Analysis of Distributional TD Learning with Linear Function Approximation
Yang Peng, Kaicheng Jin, Liangyu Zhang +1
In this paper, we study the finite-sample statistical rates of distributional temporal difference (TD) learning with linear function approximation. The aim of distributional TD lea…
Federated Control in Markov Decision Processes
Hao Jin, Yang Peng, Liangyu Zhang +1
We study problems of federated control in Markov Decision Processes. To solve an MDP with large state space, multiple learning agents are introduced to collaboratively learn its op…
Federated Reinforcement Learning with Constraint Heterogeneity
Hao Jin, Liangyu Zhang, Zhihua Zhang
We study a Federated Reinforcement Learning (FedRL) problem with constraint heterogeneity. In our setting, we aim to solve a reinforcement learning problem with multiple constraint…
Statistical Efficiency of Distributional Temporal Difference Learning and Freedman's Inequality in Hilbert Spaces
Yang Peng, Liangyu Zhang, Zhihua Zhang
Distributional reinforcement learning (DRL) has achieved empirical success in various domains. One core task in DRL is distributional policy evaluation, which involves estimating t…
Estimation and Inference in Distributional Reinforcement Learning
Liangyu Zhang, Yang Peng, Jiadong Liang +2
In this paper, we study distributional reinforcement learning from the perspective of statistical efficiency. We investigate distributional policy evaluation, aiming to estimate th…
Semi-Infinitely Constrained Markov Decision Processes and Efficient Reinforcement Learning
Liangyu Zhang, Yang Peng, Wenhao Yang +1
We propose a novel generalization of constrained Markov decision processes (CMDPs) that we call the \emph{semi-infinitely constrained Markov decision process} (SICMDP). Particularl…
Statistical Estimation of Confounded Linear MDPs: An Instrumental Variable Approach
Miao Lu, Wenhao Yang, Liangyu Zhang +1
In an Markov decision process (MDP), unobservable confounders may exist and have impacts on the data generating process, so that the classic off-policy evaluation (OPE) estimators…
Towards Theoretical Understandings of Robust Markov Decision Processes: Sample Complexity and Asymptotics
Wenhao Yang, Liangyu Zhang, Zhihua Zhang
In this paper, we study the non-asymptotic and asymptotic performances of the optimal robust policy and value function of robust Markov Decision Processes(MDPs), where the optimal…
Intervention Generative Adversarial Networks
Jiadong Liang, Liangyu Zhang, Cheng Zhang +1
In this paper we propose a novel approach for stabilizing the training process of Generative Adversarial Networks as well as alleviating the mode collapse problem. The main idea is…